Contemporary Text Input or Text editing methods enable error correction and automatic word completion as the user types text. In these existing systems, the dictionary is divided between the common language-specific dictionary and the user's own dictionary. The common dictionary contains words that belong to the used display text language. The user's own dictionary contains words that the user currently uses (e.g. proper names, nicknames, used foreign words etc.). The user dictionary learns the most commonly used words automatically. The bigger the usage frequency is, the more the word is offered to the user.
However, these known systems do not sufficiently take human behavior into account. Personal differences in writing style are partly handled by the learning user dictionary. It takes time to teach the dictionary to learn the apparatus user's personal style during use of an ambiguous keystroke disambiguation and/or word autocompletion text editor application. Further, present systems do not use context sensitive writing style. The same person may use different styles in different situations and depending on the target audience of the text. Tautology in writing in certain style is another aspect that is not taken into account. In general users do not use a large variety of words, but tend to repeat certain words.